The relational processing limits of classic and contemporary neural network models of language processing

Whether neural networks can capture relational knowledge is a matter of long-standing controversy. Recently, some researchers have argued that (1) classic connectionist models can handle relational structure and (2) the success of deep learning approaches to natural language processing suggests that structured representations are unnecessary to model human language. We tested the Story Gestalt model, a classic connectionist model of text comprehension, and a Sequence-to-Sequence with Attention model, a modern deep learning architecture for natural language processing. Both models were trained to answer questions about stories based on abstract thematic roles. Two simulations varied the statistical structure of new stories while keeping their relational structure intact. The performance of each model fell below chance at least under one manipulation. We argue that both models fail our tests because they can't perform dynamic binding. These results cast doubts on the suitability of traditional neural networks for explaining relational reasoning and language processing phenomena

Relation learning and reasoning on computational models of high level cognition

Relational reasoning is central to many cognitive processes, ranging from “lower” processes like object recognition to “higher” processes such as analogy-making and sequential decision-making. The first chapter of this thesis gives an overview of relational reasoning and the computational demands that it imposes on a system that performs relational reasoning. These demands are characterized in terms of the binding problem in neural networks. There has been a longstanding debate in the literature regarding whether neural network models of cognition are, in principle, capable of relation-base processing. In the second chapter I investigated the relational reasoning capabilities of the Story Gestalt model (St. John, 1992), a classic connectionist model of text comprehension, and a Seq-to-Seq model, a deep neural network of text processing (Bahdanau, Cho, & Bengio, 2015). In both cases I found that the purportedly relational behavior of the models was explainable by the statistics of their training datasets. We propose that both models fail at relational processing because of the binding problem in neural networks. In the third chapter of this thesis, I present an updated version of the DORA architecture (Doumas, Hummel, & Sandhofer, 2008), a symbolic-connectionist model of relation learning and inference that uses temporal synchrony to solve the binding problem. We use this model to perform relational policy transfer between two Atari games. Finally, in the fourth chapter I present a model of relational reinforcement that is able to select relevant relations, from a potentially large pool of applicable relations, to characterize a problem and learn simple rules from the reward signal, helping to bridge the gap between reinforcement learning and relational reasoning

A theory of relation learning and cross-domain generalization

People readily generalize knowledge to novel domains and stimuli. We present a theory, instantiated in a computational model, based on the idea that cross-domain generalization in humans is a case of analogical inference over structured (i.e., symbolic) relational representations. The model is an extension of the LISA and DORA models of relational inference and learning. The resulting model learns both the content and format (i.e., structure) of relational representations from non-relational inputs without supervision, when augmented with the capacity for reinforcement learning, leverages these representations to learn individual domains, and then generalizes to new domains on the first exposure (i.e., zero-shot learning) via analogical inference. We demonstrate the capacity of the model to learn structured relational representations from a variety of simple visual stimuli, and to perform cross-domain generalization between video games (Breakout and Pong) and between several psychological tasks. We demonstrate that the model's trajectory closely mirrors the trajectory of children as they learn about relations, accounting for phenomena from the literature on the development of children's reasoning and analogy making. The model's ability to generalize between domains demonstrates the flexibility afforded by representing domains in terms of their underlying relational structure, rather than simply in terms of the statistical relations between their inputs and outputs.Comment: Includes supplemental materia

A Simple Microbiome in the European Common Cuttlefish, Sepia officinalis.

The European common cuttlefish, Sepia officinalis, is used extensively in biological and biomedical research, yet its microbiome remains poorly characterized. We analyzed the microbiota of the digestive tract, gills, and skin in mariculture-raised S. officinalis using a combination of 16S rRNA amplicon sequencing, quantitative PCR (qPCR), and fluorescence spectral imaging. Sequencing revealed a highly simplified microbiota consisting largely of two single bacterial amplicon sequence variants (ASVs) of Vibrionaceae and Piscirickettsiaceae The esophagus was dominated by a single ASV of the genus Vibrio Imaging revealed bacteria in the family Vibrionaceae distributed in a discrete layer that lines the esophagus. This Vibrio was also the primary ASV found in the microbiota of the stomach, cecum, and intestine, but occurred at lower abundance, as determined by qPCR, and was found only scattered in the lumen rather than in a discrete layer via imaging analysis. Treatment of animals with the commonly used antibiotic enrofloxacin led to a nearly 80% reduction of the dominant Vibrio ASV in the esophagus but did not significantly alter the relative abundance of bacteria overall between treated versus control animals. Data from the gills were dominated by a single ASV in the family Piscirickettsiaceae, which imaging visualized as small clusters of cells. We conclude that bacteria belonging to the Gammaproteobacteria are the major symbionts of the cuttlefish Sepia officinalis cultured from eggs in captivity and that the esophagus and gills are major colonization sites.IMPORTANCE Microbes can play critical roles in the physiology of their animal hosts, as evidenced in cephalopods by the role of Vibrio (Aliivibrio) fischeri in the light organ of the bobtail squid and the role of Alpha- and Gammaproteobacteria in the reproductive system and egg defense in a variety of cephalopods. We sampled the cuttlefish microbiome throughout the digestive tract, gills, and skin and found dense colonization of an unexpected site, the esophagus, by a microbe of the genus Vibrio, as well as colonization of gills by Piscirickettsiaceae This finding expands the range of organisms and body sites known to be associated with Vibrio and is of potential significance for understanding host-symbiont associations, as well as for understanding and maintaining the health of cephalopods in mariculture

Characterization of retinal drusen in subjects at high genetic risk of developing sporadic Alzheimer’s disease: An exploratory analysis

Having a family history (FH+) of Alzheimer’s disease (AD) and being a carrier of at least one ε4 allele of the ApoE gene are two of the main risk factors for the development of AD. AD and age-related macular degeneration (AMD) share one of the main risk factors, such as age, and characteristics including the presence of deposits (Aβ plaques in AD and drusen in AMD); however, the role of apolipoprotein E isoforms in both pathologies is controversial. We analyzed and characterized retinal drusen by optical coherence tomography (OCT) in subjects, classifying them by their AD FH (FH-or FH+) and their allelic characterization of ApoE ε4 (ApoE ε4-or ApoE ε4+) and considering cardiovascular risk factors (hypercholesterolemia, hypertension, and diabetes mellitus). In addition, we analyzed the choroidal thickness by OCT and the area of the foveal avascular zone with OCTA. We did not find a relationship between a family history of AD or any of the ApoE isoforms and the presence or absence of drusen. Subjects with drusen show choroidal thinning compared to patients without drusen, and thinning could trigger changes in choroidal perfusion that may give rise to the deposits that generate drusen

Microvesicles: ROS scavengers and ROS producers

This review analyzes the relationship between microvesicles and reactive oxygen species (ROS). This relationship is bidirectional; on the one hand, the number and content of microvesicles produced by the cells are affected by oxidative stress conditions; on the other hand, microvesicles can directly and/or indirectly modify the ROS content in the extra- as well as the intracellular compartments. In this regard, microvesicles contain a pro-oxidant or antioxidant machinery that may produce or scavenge ROS: direct effect. This mechanism is especially suitable for eliminating ROS in the extracellular compartment. Endothelial microvesicles, in particular, contain a specific and well-developed antioxidant machinery. On the other hand, the molecules included in microvesicles can modify (activate or inhibit) ROS metabolism in their target cells: indirect effect. This can be achieved by the incorporation into the cells of ROS metabolic enzymes included in the microvesicles, or by the regulation of signaling pathways involved in ROS metabolism. Proteins, as well as miRNAs, are involved in this last effect

Retinal Thickness Changes Over Time in a Murine AD Model APP NL-F/NL-F.

Background: Alzheimer's disease (AD) may present retinal changes before brain pathology, suggesting the retina as an accessible biomarker of AD. The present work is a diachronic study using spectral domain optical coherence tomography (SD-OCT) to determine the total retinal thickness and retinal nerve fiber layer (RNFL) thickness in an APPNL-F/NL-F mouse model of AD at 6, 9, 12, 15, 17, and 20 months old compared to wild type (WT) animals. Methods: Total retinal thickness and RNFL thickness were determined. The mean total retinal thickness was analyzed following the Early Treatment Diabetic Retinopathy Study sectors. RNFL was measured in six sectors of axonal ring scans around the optic nerve. Results: In the APPNL-F/NL-F group compared to WT animals, the total retinal thickness changes observed were the following: (i) At 6-months-old, a significant thinning in the outer temporal sector was observed; (ii) at 15-months-old a significant thinning in the inner temporal and in the inner and outer inferior retinal sectors was noticed; (iii) at 17-months-old, a significant thickening in the inferior and nasal sectors was found in both inner and outer rings; and (iv) at 20-months-old, a significant thinning in the inner ring of nasal, temporal, and inferior retina and in the outer ring of superior and temporal retina was seen. In RNFL thickness, there was significant thinning in the global analysis and in nasal and inner-temporal sectors at 6 months old. Thinning was also found in the supero-temporal and nasal sectors and global value at 20 months old. Conclusions: In the APPNL-F/NL-F AD model, the retinal thickness showed thinning, possibly produced by neurodegeneration alternating with thickening caused by deposits and neuroinflammation in some areas of the retina. These changes over time are similar to those observed in the human retina and could be a biomarker for AD. The APPNL-F/NL-F AD model may help us better understand the different retinal changes during the progression of AD.This research was funded by the Ophthalmological Network OFTARED (RD16/0008/0005) of the Institute of Health of Carlos III of the Spanish Ministry of Science and Innovation; and the Research Network RETIBRAIN (RED2018-102499-T) and Grant PID2019-106581RB-I00 of the Spanish Ministry of Science and Innovation; and Leducq Foundation for Cardiovascular Research TNE-19CVD01. IL-C was currently supported by a Pre-doctoral Fellowship (CT42/18-CT43/18) from the Complutense University of Madrid. JF-A was currently supported by a Pre-doctoral Fellowship (FPU17/01023) from the Spanish Ministry of Science, Innovation, and Universities.S

The Symbiome of Llaveia Cochineals (Hemiptera: Coccoidea: Monophlebidae) Includes a Gammaproteobacterial Cosymbiont Sodalis TME1 and the Known Candidatus Walczuchella monophlebidarum

The genome and transcriptome of the endosymbiotic flavobacterium Candidatus Walczuchella monophlebidarum revealed its role in the synthesis of essential amino acids for its host, the wax cochineal Llaveia axin axin. There were, however, missing genes in the endosymbiont for some biosynthetic pathways. Here, we characterized TME1, another cochineal symbiont that may metabolically complement Walczuchella. TME1 was ascribed to the gammaproteobacterial genus Sodalis on a phylogenomic basis using gene sequences from 143 proteins core genome sequences and the core average nucleotide identity (ANI) confirmed its position. Additionally, we describe Sodalis as a coherent genus. TME1 genome is around 3.4 Mb and has complete gene sequences for the biosynthesis of 10 essential amino acids, for polyamines, flagella, nitrate respiration, and detoxification among many others. Transcripts from ovaries and bacteriomes allowed the identification of differentially transcribed genes from the endosymbionts and host. Highly transcribed genes were identified in TME1 and transcripts involved in amino acid biosynthesis were found. We review here that cosymbionts that derived from different bacterial classes and genera seem to be advantageous for insects that have Flavobacteria as the primary endosymbionts